Improving signal prediction performance of neural networks through multiresolution learning approach.

In this paper, we extend the original work on multiresolution learning for neural networks, and present new developments on the multiresolution learning paradigm. The contributions of this paper include: (1) proposing a new concept and method of adjustable neural activation functions in multiresolution learning to improve neural network learning efficacy and generalization performance for signal predictions; (2) providing new insightful explanations for the multiresolution learning paradigm from a multiresolution optimization perspective; (3) exploring underlying ideas why the multiresolution learning scheme associated with adjustable activation functions would be more appropriate for the multiresolution learning paradigm; and (4) providing rigorous validations to evaluate the multiresolution learning paradigm with adjustable activation functions and comparing it with the schemes of multiresolution learning with fixed activation functions and traditional learning. This paper presents systematically new analytical and experimental results on the multiresolution learning approach for training an individual neural network model, demonstrates our integral solution on neural network learning efficacy, and illustrates the significant improvements on neural networks' generalization performance and robustness for nonlinear signal predictions.     

Effect of Pressure Gradient on Heat Transfer of Impinging Submerged Circular Jets

An experimental and numerical study have been carried out to investigate the distribution of radial local heat transfer coefficients of impinging submerged circular jets. Good agreement is achieved between the experimental results and the predicted value. Results show that the outer peak usually occurs at the radial location of r/d= 1.8~2.0, in which transition from laminar to turbulence happens resulting from disappeared pressure gradient abruptly, and that the inner peak appears rigidly at r/d=0.5, where the boundary layer has a minimum thickness because of elevating pressure gradient.     

熔融-固相缩聚法中固相聚合对聚乳酸合成的影响

以L 乳酸单体为原料 ,熔融 -固相缩聚法合成了聚乳酸 ,重点研究了固相聚合的工艺条件。结果表明 ,绝对压力 60Pa ,氯化亚锡为催化剂 ,分段控温 ,可使聚乳酸的粘均分子量提高到固相聚合反应前的 5 3倍。通过对固相聚合产物的结晶度和熔点的分析 ,探讨了固相聚合的机理。     

Automatic conversion from lexical words to prosodic words for mandarin text-to-speech system

In real speech, not like lexical words (LWs), prosodic words (PWs) are basic rhythmic units. The naturalness of a Text-to-Speech (TTS) system is directly influenced by the segmentation of the PWs. Most of the PWs are the combination of several LWs. In this paper, three Lexical Combination Models are proposed to combine LWs into PWs, including a Directed Acyclic Graph Model, a Segmentation Model and a Markov Model (MM). To cope with the situation where some long LWs should be segmented into two or more PWs, a Lexical Split Model (LSM) is applied to the long LWs. Experimental results prove that relatively constant results with various training data can be obtained from a MM. The Transformation-Based Error Driven Learning (TBED) algorithm, for its high performance of individual property, is applied in combination with the MM to improve the precision of PW segmentation. Experiments show that among the three proposed models, the MM combined with TBED and LSM, leads to the best performance, in which a precision of 93.00% and a recall of 93.23% are achieved. The perception test indicates that by using PWs as the lowest prosodic units a speech sounds more natural and acceptable than by using LWs. This paper is supported by NSFC Project (60503071); 973 Natural Basic Research Program of China (2004CB318102); Postdoctor Science Foundation of P. R. China (20070420275).     

A Constraint-based Approach for Annotating Music Scores with Gestural Information

The physical gestures that operate music instruments are responsible for the qualities of the sound being produced in a performance. Gestural information is thereby crucial for a model of music performance, paired with a model of sound synthesis where this information is applied. The highly constrained nature of performers gestures makes this task suitable to be modeled via a constraint-based approach, coupled with a strategy aimed at maximizing the gestural comfort of performers. We illustrate the problem representation, the search strategy and a validation of the model against human performance.     

Multibody simulation tool for the calculation of lashing loads on RoRo ships

Approximately 80% of the international transport of goods is carried on by means of ships. A large portion of the transport capacity is represented by Roll-on-Roll-off (RoRo) ships. Especially in Europe this is a relevant potential for the RoRo segment. Consequently, the design and construction of RoRo ships plays an increasing role for German shipyards and their suppliers. In order to make the loading and unloading procedure of trailer economically more competitive, ship owners would like to improve the lashing of trailers on the ship. On the basis of a multibody system formalism, a software tool has been developed which allows for an optimization of the loading of trailers on RoRo ships. Commemorative Contribution.     

Formulation for Reliable Analysis of Structural Frames

Structural engineers use design codes formulated to consider uncertainty for both reinforced concrete and structural steel design. For a simple one-bay structural steel frame, we survey typical uncertainties and compute an interval solution for displacements and forces. The naive solutions have large over-estimations, so we explore the Mullen-Muhanna assembly strategy, scaling, and constraint propagation to achieve tight enclosures of the true ranges for displacements and forces in a fraction of the CPU time typically used for simulations. That we compute tight enclosures, even for large parameter uncertainties used in practice, suggests the promise of interval methods for much larger structures.     

SCC casting prediction for the realization of prototype VHPC-precambered composite beams

Casting simulations of self-compacting concrete are carried out in order to obtain a value of the minimum fluidity needed to cast a VHPC precambered composite beam. The mix proportioning of the concrete takes into account this minimum value. The numerical predictions are finally compared with the experimental observations during two casting tests and the real casting of the two 13 m beams. Although the simplifying assumptions needed to carry out the simulations are numerous, there is an agreement between the predictions and the real casting.     

Critical Configurations for 1-View in Projections from ℙ<Superscript>k</Superscript> → ℙ<Superscript>2</Superscript>

In this paper we describe, from a theoretical point of view, critical configurations for the projective reconstruction of a set of points, for a single view, i.e. for calibration of a camera, in the case of projections from ℙ^k to ℙ² for k ≥ 4. We give first a general result describing these critical loci in ℙ^k, which, if irreducible, are algebraic varieties of dimension k−2 and degree 3. If k=4 they can be either a smooth ruled surface or a cone and if k = 5 they can be a smooth three dimensional variety, ruled in planes, or a cone. If k≥ 6, the variety is always a cone, the vertex of which has dimension at least k − 6. The reducible cases are studied in Appendix A. These results are then applied to determine explicitly the critical loci for the projections from ℙ^k which arise from the dynamic scenes in ℙ³ considered in [13]. Marina Bertolini is currently Associate Professor of Geometry at the Department of Mathematics at the Università degli Studi di Milano, Italy. Her main field of research is Complex Projective Algebraic Geometry, with particular interest for the classification of projective varieties and for the geometry of Grassmann varieties. On these topics M. Bertolini has published more than twenty reviewed papers on national and international journals. She has been for some years now interested also in applications of Algebraic Geometry to Computer Vision problems. Cristina Turrini is Associate Professor of Geometry at the Department of Mathematics of Università degli Studi di Milano, Italy. Her main research interest is Complex Projective Algebraic Geometry: subvarieties of Grassmannians, special varieties, automorphisms, classification. In the last two years she has started to work on applications of Algebraic Geometry to problems of Computer Vision. She is author or co-author of about thirty reviewed papers. She is also involved in popularization of Mathematics, and on this subject she is co-editor of some books.